this post was submitted on 12 Dec 2023
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AI
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Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen.
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Note: the actual paper's title ends in a question mark and states in its "discussion":
It is clear to anyone who used them and understand the task they were trained on, that LLMs do have emergent abilities. This paper is a refutation of precise claims of other papers that they argue use inappropriate metric to show "sudden" emergence rather than a "smooth" one.
This paper is a precise refutation to all current claims of emergence as nothing more than bad measurements.
Not by the definition in this paper they don't. They show linear improvement which is not emergent. The definition used is:
The capabilities displayed by LLMs all fall on a linear progression when you use the correct measures. That is the antithetical to emergent behaviors.
Again: that does not preclude emergence in the future, but it strongly refutes present claims of emergence.
That's a weird definition. Is it a widely used one? To me emergence meant to acquire capabilities not specifically trained for. I don't see why them appearing suddenly or linearly is important? I guess that's an argument in safety discussions?
It's not the definition in the paper. Here is the context:
What this means is, that we cannot, for example, predict chemistry from physics. Physics studies how atoms interact, which yields important insights for chemistry, but physics cannot be used to predict, say, the table of elements. Each level has its own laws, which must be derived empirically.
LLMs obviously show emergence. Knowing the mathematical, technological, and algorithmic foundation, tells you little about how to use (prompt, train, ...) an AI model. Just like knowing cell biology will not help you interact with people, even if they are only colonies of cells working together.
The paper talks specifically about “emergent abilities of LLMs”:
The authors further clarify:
Bigger models perform better. An increase in the number of parameters correlates to an increase in the performance on tests. It had been alleged, that some abilities appear suddenly, for no apparent reason. These “emergent abilities of LLMs” are a very specific kind of emergence.